数千人の専門家で構成された権威ある制作チームが、AAIR学習の質問を理解し、質の高い学習体験を楽しんでいます。 試験概要と現在のポリシーの最近の変更に応じて、AAIRテストガイドの内容を随時更新します。 また、AAIR試験の質問は、わかりにくい概念を簡素化して学習方法を最適化し、習熟度を高めるのに役立ちます。 さらに、AAIRテストガイドを使用すると、試験を受ける前に20〜30時間の練習で準備時間を短縮できることは間違いありません。
| Section | Objectives |
|---|---|
| AI Lifecycle Controls | - Controls across AI development lifecycle
|
| Regulatory and Compliance Requirements | - Global AI regulatory landscape
|
| AI Risk Management | - Risk identification and assessment for AI systems
|
| AI Governance and Strategy | - AI governance frameworks and organizational oversight
|
| Ethics, Privacy, and Responsible AI | - Ethical AI principles and compliance
|
各国の人はAAIR復習資料を利用できるために、私たちの専門家は全力を尽くしてAAIR復讐資料の内容を簡潔化し、詳しい説明を添えました。従って、AAIR復習資料を楽的に利用できるようになりました。大切なのは、AAIR復習資料の合格率が高いで、多くの受験者がAAIR試験をパスしたということです。それは、私たちの誇りです。
質問 # 59
Which of the following information is MOST important to add to an organizational business continuity plan (BCP) when adopting a customer-facing AI solution?
正解：B
解説：
Business continuity planning for customer-facing AI solutions must ensure service availability and resilience under failure conditions. The BCP must specify the technical and operational mechanisms that maintain service continuity when primary systems are disrupted.
Why B is Correct: The ISACA AAIR business continuity guidance identifies secure access to alternate resources, multi-region failover, and load balancing as the most important additions to a BCP for customer- facing AI. These mechanisms ensure that service disruptions-whether from technical failures, cyber incidents, or regional outages-do not result in total unavailability. For customer-facing solutions, maintaining service continuity directly affects customer trust, revenue, and regulatory compliance with service availability obligations.
Why A is Wrong: Post-incident audits of recovery times and accuracy metrics are monitoring activities that occur after incidents. While valuable for improvement planning, they do not define the recovery mechanisms that the BCP must specify to ensure continuity during disruptions.
Why C is Wrong: Centralizing failover under a single cloud provider creates a concentration risk-if that provider experiences an outage, all failover mechanisms fail simultaneously. Good BCP design requires geographic and provider diversification, not concentration.
Why D is Wrong: Breach containment criteria address security incident response, not service continuity.
While related to incident management, breach response procedures are typically documented in the incident response plan rather than the BCP, which focuses on maintaining or restoring business operations.
質問 # 60
Which AI security by design option BEST mitigates targeted model poisoning and supply chain tampering?
正解：D
解説：
Model poisoning attacks target the training data or model parameters to degrade performance or introduce malicious behavior. Supply chain tampering introduces compromised components at vendor or integration stages. Security by design principles require embedding defenses against these threats from the earliest design stages.
Why C is Correct: According to ISACA AAIR security by design guidance, adversarial resilience and data integrity controls address both model poisoning and supply chain tampering at their root. Adversarial resilience training prepares the model to resist maliciously crafted inputs. Data integrity controls- cryptographic signing, provenance tracking, integrity verification-detect tampering in training data and model artifacts across the supply chain. Together, these form the most comprehensive defense against both attack categories.
Why A is Wrong: Data refreshes with checksums detect post-hoc data corruption but do not build adversarial resilience into the model itself. Checksums verify file integrity but cannot prevent poisoning attacks that maintain file integrity while altering data content.
Why B is Wrong: Frequent retraining and bias monitoring address performance drift and fairness but do not specifically protect against deliberate tampering. A retrained model may still be trained on poisoned data if integrity controls are absent.
Why D is Wrong: Data tokenization protects sensitive field values from unauthorized access (a privacy control) but does not address model poisoning or supply chain tampering, which can occur without accessing or exposing the sensitive field values themselves.
質問 # 61
An organization plans to deploy a generative AI system that processes sensitive personal data across multiple countries with varying privacy laws. Which of the following is the BEST course of action to manage legal and regulatory exposure?
正解：A
解説：
Multi-jurisdictional AI deployment requires jurisdiction-specific compliance strategies because privacy and data protection laws vary significantly across countries. A one-size-fits-all approach frequently fails to meet local requirements, while post-deployment remediation creates legal exposure during the gap period.
Why B is Correct: According to ISACA AAIR guidance, the best approach to multi-jurisdictional compliance is to tailor controls to each relevant statutory framework before deployment and maintain audit trails that demonstrate adherence. This proactive, documented approach reduces legal exposure, satisfies regulatory examination requirements, and enables the organization to demonstrate accountability-a key requirement of frameworks like GDPR.
Why A is Wrong: Post-deployment remediation means the organization is non-compliant during deployment, which creates immediate regulatory exposure. Iterative fixes after harm has occurred are inadequate for protecting individuals or the organization.
Why C is Wrong: Uniform global policies cannot satisfy jurisdictions with conflicting requirements-some laws mandate data residency within borders, making cross-border transfer impossible regardless of encryption strength.
Why D is Wrong: Restricting disclosure of model operations conflicts with transparency requirements embedded in many privacy laws, including GDPR's right to explanation. IP protection cannot override regulatory disclosure obligations.
質問 # 62
A risk practitioner reviews an AI model that ingests diverse external feeds and determines that their reliability is not consistent. Which of the following BEST mitigates this risk?
正解：A
解説：
Inconsistent data reliability from external feeds undermines model accuracy and creates auditability challenges. The solution requires both understanding where data comes from (provenance) and verifying its quality before it enters the model's learning process (stage gate reviews).
Why C is Correct: The ISACA AAIR data quality governance guidance identifies establishing data provenance and implementing stage gate quality reviews as the comprehensive approach to managing inconsistent external data reliability. Provenance tracking records the origin, processing history, and chain of custody of each data source, enabling quality issues to be traced to their source. Stage gate reviews enforce quality standards at defined points in the data pipeline, preventing unreliable data from advancing to model training.
Why A is Wrong: Weighting historical data over recent samples introduces temporal bias and prevents the model from reflecting current real-world conditions-the opposite of what most AI applications require. This trade-off may be appropriate in specific contexts but is not a general mitigation for inconsistent data reliability.
Why B is Wrong: Updating model versions improves model architecture and training processes but does not resolve the underlying external data quality problems. The model update cannot compensate for ingesting unreliable data.
Why D is Wrong: Reducing data source diversity sacrifices the breadth of information that diverse feeds provide, potentially reducing model performance and representativeness. The goal is to ensure consistent quality from diverse sources, not to reduce diversity.
質問 # 63
AI tools can BEST help to mitigate supply chain risk by:
正解：D
解説：
Supply chain risk management requires anticipating disruptions before they materialize. AI's most powerful supply chain contribution is its ability to analyze vast datasets-including signals from suppliers, logistics networks, geopolitical indicators, and environmental data-to predict disruptions with accuracy and lead time that human analysts cannot achieve.
Why B is Correct: The ISACA AAIR AI capability guidance identifies predictive disruption identification as the most significant supply chain risk mitigation AI provides. By processing diverse data signals and identifying patterns that precede supply chain failures, AI enables proactive risk management-allowing organizations to pre-position inventory, identify alternative suppliers, or adjust production schedules before disruptions affect operations.
Why A is Wrong: Automating inventory management is an operational efficiency application. While valuable, it manages existing stock levels rather than predicting and preventing supply disruptions.
Automation cannot anticipate future risks not embedded in current inventory patterns.
Why C is Wrong: Historical security control gap identification is a security audit function. Identifying past security weaknesses does not directly mitigate supply chain disruption risks, which may arise from entirely different categories of risk.
Why D is Wrong: Sentiment analysis on supplier reputation provides one qualitative input to supplier risk assessment. While useful for monitoring reputational signals, it captures only a narrow dimension of supply chain risk compared to comprehensive predictive disruption modeling.
質問 # 64
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